/* * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ using System; using System.Collections.Generic; using System.Linq; using System.Reflection; using QuantConnect.Data; using QuantConnect.Interfaces; using QuantConnect.Orders; using QuantConnect.Securities; namespace QuantConnect.Algorithm.CSharp { /// /// This regression algorithm tests In The Money (ITM) future option expiry for short puts. /// We expect 3 orders from the algorithm, which are: /// /// * Initial entry, sell ES Put Option (expiring ITM) /// * Option assignment, buy 1 contract of the underlying (ES) /// * Future contract expiry, liquidation (sell 1 ES future) /// /// Additionally, we test delistings for future options and assert that our /// portfolio holdings reflect the orders the algorithm has submitted. /// public class FutureOptionShortPutITMExpiryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private Symbol _es19m20; private Symbol _esOption; private Symbol _expectedContract; public override void Initialize() { SetStartDate(2020, 1, 5); SetEndDate(2020, 6, 30); // We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872 // which causes delisting events to never be processed, thus leading to options that might never // be exercised until the next data point arrives. AddEquity("AAPL", Resolution.Daily); _es19m20 = AddFutureContract( QuantConnect.Symbol.CreateFuture( Futures.Indices.SP500EMini, Market.CME, new DateTime(2020, 6, 19)), Resolution.Minute).Symbol; // Select a future option expiring ITM, and adds it to the algorithm. _esOption = AddFutureOptionContract(OptionChainProvider.GetOptionContractList(_es19m20, Time) .Where(x => x.ID.StrikePrice <= 3400m && x.ID.OptionRight == OptionRight.Put) .OrderByDescending(x => x.ID.StrikePrice) .Take(1) .Single(), Resolution.Minute).Symbol; _expectedContract = QuantConnect.Symbol.CreateOption(_es19m20, Market.CME, OptionStyle.American, OptionRight.Put, 3400m, new DateTime(2020, 6, 19)); if (_esOption != _expectedContract) { throw new Exception($"Contract {_expectedContract} was not found in the chain"); } Schedule.On(DateRules.Tomorrow, TimeRules.AfterMarketOpen(_es19m20, 1), () => { MarketOrder(_esOption, -1); }); } public override void OnData(Slice data) { // Assert delistings, so that we can make sure that we receive the delisting warnings at // the expected time. These assertions detect bug #4872 foreach (var delisting in data.Delistings.Values) { if (delisting.Type == DelistingType.Warning) { if (delisting.Time != new DateTime(2020, 6, 19)) { throw new Exception($"Delisting warning issued at unexpected date: {delisting.Time}"); } } if (delisting.Type == DelistingType.Delisted) { if (delisting.Time != new DateTime(2020, 6, 20)) { throw new Exception($"Delisting happened at unexpected date: {delisting.Time}"); } } } } public override void OnOrderEvent(OrderEvent orderEvent) { if (orderEvent.Status != OrderStatus.Filled) { // There's lots of noise with OnOrderEvent, but we're only interested in fills. return; } if (!Securities.ContainsKey(orderEvent.Symbol)) { throw new Exception($"Order event Symbol not found in Securities collection: {orderEvent.Symbol}"); } var security = Securities[orderEvent.Symbol]; if (security.Symbol == _es19m20) { AssertFutureOptionOrderExercise(orderEvent, security, Securities[_expectedContract]); } else if (security.Symbol == _expectedContract) { AssertFutureOptionContractOrder(orderEvent, security); } else { throw new Exception($"Received order event for unknown Symbol: {orderEvent.Symbol}"); } Log($"{orderEvent}"); } private void AssertFutureOptionOrderExercise(OrderEvent orderEvent, Security future, Security optionContract) { if (orderEvent.Message.Contains("Assignment")) { if (orderEvent.FillPrice != 3400) { throw new Exception("Option was not assigned at expected strike price (3400)"); } if (orderEvent.Direction != OrderDirection.Buy || future.Holdings.Quantity != 1) { throw new Exception($"Expected Qty: 1 futures holdings for assigned future {future.Symbol}, found {future.Holdings.Quantity}"); } } if (!orderEvent.Message.Contains("Assignment") && orderEvent.Direction == OrderDirection.Sell && future.Holdings.Quantity != 0) { // We buy back the underlying at expiration, so we expect a neutral position then throw new Exception($"Expected no holdings when liquidating future contract {future.Symbol}"); } } private void AssertFutureOptionContractOrder(OrderEvent orderEvent, Security option) { if (orderEvent.Direction == OrderDirection.Sell && option.Holdings.Quantity != -1) { throw new Exception($"No holdings were created for option contract {option.Symbol}"); } if (orderEvent.IsAssignment && option.Holdings.Quantity != 0) { throw new Exception($"Holdings were found after option contract was assigned: {option.Symbol}"); } } /// /// Ran at the end of the algorithm to ensure the algorithm has no holdings /// /// The algorithm has holdings public override void OnEndOfAlgorithm() { if (Portfolio.Invested) { throw new Exception($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}"); } } /// /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm. /// public bool CanRunLocally { get; } = true; /// /// This is used by the regression test system to indicate which languages this algorithm is written in. /// public Language[] Languages { get; } = { Language.CSharp, Language.Python }; /// /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm /// public Dictionary ExpectedStatistics => new Dictionary { {"Total Trades", "3"}, {"Average Win", "10.18%"}, {"Average Loss", "-8.02%"}, {"Compounding Annual Return", "2.773%"}, {"Drawdown", "0.500%"}, {"Expectancy", "0.135"}, {"Net Profit", "1.343%"}, {"Sharpe Ratio", "0.939"}, {"Probabilistic Sharpe Ratio", "46.842%"}, {"Loss Rate", "50%"}, {"Win Rate", "50%"}, {"Profit-Loss Ratio", "1.27"}, {"Alpha", "0.023"}, {"Beta", "0.002"}, {"Annual Standard Deviation", "0.025"}, {"Annual Variance", "0.001"}, {"Information Ratio", "1.45"}, {"Tracking Error", "0.173"}, {"Treynor Ratio", "14.62"}, {"Total Fees", "$7.40"}, {"Fitness Score", "0.021"}, {"Kelly Criterion Estimate", "0"}, {"Kelly Criterion Probability Value", "0"}, {"Sortino Ratio", "79228162514264337593543950335"}, {"Return Over Maximum Drawdown", "5.815"}, {"Portfolio Turnover", "0.022"}, {"Total Insights Generated", "0"}, {"Total Insights Closed", "0"}, {"Total Insights Analysis Completed", "0"}, {"Long Insight Count", "0"}, {"Short Insight Count", "0"}, {"Long/Short Ratio", "100%"}, {"Estimated Monthly Alpha Value", "$0"}, {"Total Accumulated Estimated Alpha Value", "$0"}, {"Mean Population Estimated Insight Value", "$0"}, {"Mean Population Direction", "0%"}, {"Mean Population Magnitude", "0%"}, {"Rolling Averaged Population Direction", "0%"}, {"Rolling Averaged Population Magnitude", "0%"}, {"OrderListHash", "980293281"} }; } }